• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.499-505
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• 2004

In this paper, we studied about AGVs modeling and material handling automation simulation using a virtual AGV. The proposed virtual AGV model that operates independently each other is based on a real AGV. Continuous straight-line and workstation model using vector drawing method that could easily, rapidly work system modeling are suggested. Centralized traffic control, which could collision avoidance in intersection and should not stop AGV as possible, and algorithm for detour routing which performs when another AGV is working in pre-routed path are proposed. The traffic control and the algorithm have been proved efficience by simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.937-943
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• 2009

In this paper, the algorithm discriminating the existence and nonexistence of bolts and nuts using image processing in an automobile T-Bar influencing the vibration of a frame, is introduced. To distinct whether bolts and nuts exist or not, the features of bolts and nuts are learned, and then these feature values are matched using a statistical pattern matching algorithm. Furthermore, the minimum and maximum variation rate of pixel values are used since the matching rate is low with the large variation of pixel values of bolts and nuts in each image. The proposed method in this paper is very efficient in the automation of inspection requiring real time since the inspection time is significantly reduced compared with the conventional methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.287-294
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• 2019

With the automation of production lines in the manufacturing industry, the importance of real-time fault diagnosis of facility is increasing. In this paper, we propose a fault diagnosis algorithm of LM (Linear Motion)-guide based on deep learning using vibration signals. Generally, in order to guarantee the performance of the deep learning, it is necessary to have a sufficient amount of data, but in a manufacturing industry, it is often difficult to obtain enough data due to physical and time constraints. To solve this problem, we propose a convolutional neural networks (CNN) model based on transfer learning. In addition, the spectrogram image is input to the CNN to reflect the frequency characteristic of the vibration signals with time. The performance of fault diagnosis according to various load condition and transfer learning method was compared and evaluated by experiments. The results showed that the proposed algorithm exhibited an excellent performance.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.589-594
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• 1991

Group Technology (GT) is a technique for identifying and bringing together related or similar components in a production process in order to take advantage of their similarities by making use of, for example, the inherent economies of flow production methods. The process of identification, from large variety and total of components, of the part families requiring similar manufacturing operations and forming the associated groups of machines is referred as 'machine-component grouping'. First part of this paper is devoted to describing a hierarchical divisive algorithm based on graph theory to find the natural part families. The objective is to form components into part families such that the degree of inter-relations is high among components within the same part family and low between components of different part families. Second part of this paper focuses on establishing cell design procedures. The aim is to create cells in which the most expensive and important machines-called key machine - have a reasonably high utilization and the machines should be allocated to minimize the intercell movement of machine loads. To fulfil the above objectives, 0-1 integer programming model is developed and the solution procedures are found. Next an attempt is made to test the feasibility of the proposed method. Several different problems appearing in the literature are chosen and the results air briefly showed.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.3
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• pp.69-77
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• 2016

Maximum utilization of unused license spectrum is one of key factor in cognitive radio network which can handle the large number of systems and devices connected on smart grid AMI network. The central intelligence control system has responsibility to accept new technologies and users for automation. To ensure a reliable communication in smart grid system through cognitive network, a minimum mean square error (MSE) signal using unused licensed spectrum (or frequency) is necessary to be detected with small decision error. In this paper, we introduce a user control wireless smart grid system with minimum MSE using LMS algorithm.

• International Journal of Control, Automation, and Systems
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• v.1 no.4
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• pp.495-502
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• 2003

This paper focuses on the implementation of an efficient tracking method of a moving object using optimal representative blocks by way of a pan-tilt camera. The key idea is derived from the fact that when the image size of a moving object is shrunk in an image frame according to the distance between the mobile robot camera and the object in motion, the tracking performance of a moving object can be improved by reducing the size of representative blocks according to the object image size. Motion estimations using Edge Detection (ED) and Block-Matching Algorithm (BMA) are regularly employed to track objects by vision sensors. However, these methods often neglect the real-time vision data since these schemes suffer from heavy computational load. In this paper, a representative block able to significantly reduce the amount of data to be computed, is defined and optimized by changing the size of representative blocks according to the size of the object in the image frame in order to improve tracking performance. The proposed algorithm is verified experimentally by using a two degree-of- freedom active camera mounted on a mobile robot.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.6
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• pp.28-36
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• 2001

A robust adaptive sliding mode robot control algorithm is derived, which consists of a feed-forward compensation part and discontinuous control part. The unknown parameters is categorized into two groups, with group containing the parameters estimated on-line, and group containing the parameters not estimated on-line. Then a sliding control term is incorporated into the torque input in order to account for the effects of uncertainties on the parameters not estimated on-line and of disturbances. Moreover, the algorithm is computationally simple, due to an effective exploitation of the structure of manipulator dynamics. It is shown that, despite the existence of the parameter uncertainty and external disturbances, the controller is globally asymptotically stable and guarantees zero tracking errors.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.401-405
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• 2005

In this paper, we designed data transformation interface for the automation of PCB product. The data designed to CAD does not exchange itself for the assembly line, so we analyzed the information of PCB components designed to CAD and developed human error detect algorithm. We also constructed database for the information of IC components. Developed the algorithm can change to the data suitable for the assembly line of PCB and this system was designed to do addition and revision of the components through the user interface. By automating existing manual processing, we were able to shorten the time of 1-2 days to several minutes and enhance reliability of the data and the efficient assembly line of PCB.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.281-287
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• 2010

This study compares transformation algorithms for co-registration of terrestrial laser scan data. Pair-wise transformation which is used for transformation of scan data from more than two different view accumulates errors. ICP algorithm commonly used for co-registration between scan data needs initial geometry information. And it is difficult to co-register simultaneously because of too many control points when managing scan at the same time. Therefore, this study perform global registration technique using matching points. Matching points are extracted automatically from intensity image by SIFT and global registration is performed using GP analysis. There are advantages for operation speed, accuracy, automation in suggested global registration algorithm. Through the result from it, registration algorithms can be developed by considering accuracy and speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1926-1945
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• 2014

In this paper, we propose a distributed signal subspace interference alignment algorithm for single beam K-user ($3K{\geq}$) MIMO interference channel based on sum rate maximization and game theory. A framework of game theory is provided to study relationship between interference signal subspace and altruistic-egoistic bayesian game cost function. We demonstrate that the asymptotic interference alignment under proposed scheme can be realized through a numerical algorithm using local channel state information at transmitters and receivers. Simulation results show that the proposed scheme can achieve the total degrees of freedom that is equivalent to the Cadambe-Jafar interference alignment algorithms with perfect channel state information. Furthermore, proposed scheme can effectively minimize leakage interference in desired signal subspace at each receiver and obtain a moderate average sum rate performance compared with several existing interference alignment schemes.